Modeling human-agent interaction using bayesian network technique

Yukiko Nakano, Kazuyoshi Murata, Mika Enomoto, Yoshiko Arimoto, Yasuhiro Asa, Hirohiko Sagawa

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Task manipulation is direct evidence of understanding, and speakers adjust their utterances that are in progress by monitoring listener's task manipulation. Aiming at developing animated agents that control multimodal instruction dialogues by monitoring users' task manipulation, this paper presents a probabilistic model of fine-grained timing dependencies among multimodal communication behaviors. Our preliminary evaluation demonstrated that our model quite accurately judges whether the user understand the agent's utterances and predicts user's successful mouse manipulation, suggesting that the model is useful in estimating user's understanding and can be applied to determining the next action of an agent.

本文言語English
ホスト出版物のタイトルNew Frontiers in Artificial Intelligence - JSAI 2007 Conference and Workshops, Revised Selected Papers
ページ5-12
ページ数8
DOI
出版ステータスPublished - 2008
イベント21st Annual Conference of The Japanese Society for Artificial Intelligence, JSAI 2007 - Miyazaki, Japan
継続期間: 2007 6月 182007 6月 22

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4914 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other21st Annual Conference of The Japanese Society for Artificial Intelligence, JSAI 2007
国/地域Japan
CityMiyazaki
Period07/6/1807/6/22

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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